Energy-saving methodology for material handling applications

This paper presents an energy saving approach to the problem of order picking in warehousing environment, which is directly related to the well-known Traveling Salesman Problem (TSP). While the available heuristic algorithms for the order-picking problem search for the route that minimizes the trave...

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Published inApplied energy Vol. 83; no. 10; pp. 1116 - 1124
Main Authors Makris, P.A., Makri, A.P., Provatidis, C.G.
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 01.10.2006
Elsevier Science
Elsevier
SeriesApplied Energy
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Abstract This paper presents an energy saving approach to the problem of order picking in warehousing environment, which is directly related to the well-known Traveling Salesman Problem (TSP). While the available heuristic algorithms for the order-picking problem search for the route that minimizes the travel time, here the problem is addressed from the energy saving point of view. In a few words, the least energy-consuming route is identified in order to quantify the trade off in time and energy between the fastest route and the most energy economic one. Keeping in mind that often energy is as important as time, especially during a low-demand period, the current paper sheds some light into a two dimensional way of addressing the warehouse material handling problem, which saves time as well as energy. A very interesting finding is that a relatively small loss of service time in many cases may lead to a significant decrease of consumed energy without any additional cost.
AbstractList This paper presents an energy saving approach to the problem of order picking in warehousing environment, which is directly related to the well-known Traveling Salesman Problem (TSP). While the available heuristic algorithms for the order-picking problem search for the route that minimizes the travel time, here the problem is addressed from the energy saving point of view. In a few words, the least energy-consuming route is identified in order to quantify the trade off in time and energy between the fastest route and the most energy economic one. Keeping in mind that often energy is as important as time, especially during a low-demand period, the current paper sheds some light into a two dimensional way of addressing the warehouse material handling problem, which saves time as well as energy. A very interesting finding is that a relatively small loss of service time in many cases may lead to a significant decrease of consumed energy without any additional cost.
The energy saving approach to the problem of order picking in warehousing environment, which is directly related to the well-known Traveling Salesman Problem (TSP), is presented. While the available heuristic algorithms for the order-picking problem search for the route that minimizes the travel time, here the problem is addressed from the energy saving point of view. In a few words, the least energy-consuming route is identified in order to quantify the trade off in time and energy between the fastest route and the most energy economic one. A very interesting finding is that a relatively small loss of service time in many cases may lead to a significant decrease of consumed energy without any additional cost.
Author Makris, P.A.
Provatidis, C.G.
Makri, A.P.
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Cites_doi 10.1016/S0377-2217(99)00020-X
10.1016/S0307-904X(02)00137-3
10.1016/S0360-8352(02)00058-X
10.1080/07408179008964179
10.1016/0167-6377(82)90012-8
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Issue 10
Keywords Energy saving
Warehouse
Order picking
Energy consumption
Methodology
Energy conservation
Heuristic approach
Algorithm
Application
Handling
Language English
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Snippet This paper presents an energy saving approach to the problem of order picking in warehousing environment, which is directly related to the well-known Traveling...
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SubjectTerms Applied sciences
Energy
Energy saving
Energy saving Order picking Warehouse
Energy. Thermal use of fuels
Exact sciences and technology
Order picking
Rational use of energy: conservation and recovery of energy
Warehouse
Title Energy-saving methodology for material handling applications
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